Study design
This was a pre-registered single-centre parallel group randomized controlled trial with pre-intervention (T0), post-intervention (T1), 5-weeks post-intervention retention (T2) and 1-year post-intervention follow-up (T3) tests. Participants were randomly assigned to either five weeks of CT or FP.
Randomization
After giving informed consent, participants were randomly assigned to one of the two interventions using an automated, custom-made minimization algorithm written in MATLAB. This minimization of group differences used time after stroke, age and FAC score as stratifying factors, which together determined 80% of group allocation. Due to the nature of the intervention the assessors, physical therapists and participants were not blinded to group allocation.
Participants
Participants were recruited from the outpatient population of rehabilitation center Reade (Amsterdam, the Netherlands). A sample size calculation was carried out that resulted in a sample size of 14 participants in each group to achieve 80% power with a two-tailed α of 0.05. Considering a drop out of 10–25%, we decided to recruit 20 participants in each group, resulting in a total of 40 participants [24]. All participants had suffered a first-ever ischemic stroke ≥ 3 months before study entrance, had a Functional Ambulation Categories (FAC) score ≥ 4, were clinically diagnosed with hemiparesis and suffered from walking and/or balance deficits established by a physician. Exclusion criteria were orthopedic and other neurological disorders that affect walking (e.g., Parkinson’s disease), other treatments that could influence the effects of the interventions (e.g., recent Botulin toxin treatment of the lower extremity), contra-indication to physical activity (e.g., heart failure, severe osteoporosis), moderate or severe cognitive impairments as indicated by a Mini-Mental State Examination score below 21, severe uncorrected visual deficits, or inability to understand and execute simple instructions [24]. All participants provided written informed consent before the start of the trial. The protocol for the study was approved by the Medical Ethical Reviewing Committee of the VU University Medical Centre (Amsterdam, the Netherlands; protocol number 2013/53 and the Central Committee on Research Involving Human Subjects, CCMO, protocol number NL 42461.029.13).
Interventions: treadmill-based C-Mill therapy (CT) and overground FALLS program (FP)
CT is a treadmill-based training with a specific emphasis on practicing walking adaptability, using gait-dependent projector-generated context on the instrumented treadmill surface to elicit step adjustments. CT encompasses various exercises to practice avoidance of projected visual obstacles, foot positioning on a step-to-step basis to regular or irregular sequences of visual stepping targets (goal-directed stepping) with or without obstacles, gait acceleration and deceleration by maintaining position within a projected walking area that moves along the treadmill, walking with tandem steps, and an interactive walking-adaptability game [8, 12]. C-Mill therapy is a patient-tailored type of training in that the therapist can adjust the difficulty of the different exercises by manipulating content parameters as the obstacle size or available response time for obstacle negotiation. Therapists were encouraged to increase the level of difficulty as tolerated by the participant by either changing content parameters or increasing the belt speed.
FP is an overground walking therapy program aimed at reducing the number of falls in people after stroke by including walking-adaptability exercises. The program incorporates an obstacle course consisting of exercises to practice obstacle avoidance, foot positioning while walking over uneven terrain, tandem walking, and slalom walking. Therapists in this program are encouraged to increase the level of difficulty by adding cognitive and motor dual-tasks or to use visual constraints, as described in the pre-defined training protocol [9]. The program also incorporates exercises to simulate walking in a crowded environment and to practice falling techniques (one session per week).
Both interventions were matched in therapy session duration (90 min), frequency (twice per week). CT group trained in groups of two participants and the FP group trained in groups of 4–6 participants. Participants in both groups alternately trained and rested and had similar therapist attention (mean participant-to-therapist ratio, 2:1). Further details of the interventions can be found in the study protocol [24].
Procedure & set-ups
At T0, T1, T2 and T3, participants performed three different walking tasks (see [24, 27] for more details): the standard 10MWT [25], and two context-specific assessments: 1) 10MWT with stationary physical context (10MWT context) and 2) Interactive Walkway assessments with suddenly appearing projected obstacles in a gait-dependent manner (IWW obstacles) [23, 26], all with and without the simultaneous performance of a cognitive task. This resulted in six walking conditions, which were performed in a randomized order. The standard 10MWT and 10MWT context were performed three times at a self-selected comfortable walking speed (Fig. 2A-2B). The 10MWT context comprised three physical obstacles, a tandem-walking path and three stepping targets. Participants were instructed to step over the obstacles, step onto the targets and in-between the tandem-path lines. To assess walking adaptability under time pressure, the IWW obstacles comprised two suddenly appearing visual obstacles in the form of a projected red rectangle, presented in both a gait-dependent (at a predicted foot-placement position) and a position-dependent (at an unpredictable but predefined position) manner. Ten runs were performed, including three dummy trials without obstacles (to retain unpredictability), at a self-selected comfortable walking speed (Fig. 2C). Participants were instructed to step over the suddenly appearing projected obstacle images.
The cognitive dual-task was a serial-3 subtraction task, which had to be performed by counting backwards out loud. The number to start with was varied to avoid task-familiarization. Participants practiced this subtraction task for 30s while sitting. During all dual-task conditions, participants were instructed to simultaneously perform both tasks as effectively as possible at a self-selected walking speed. Additionally, a 60s subtraction task was performed while sitting to determine the degree of cognitive motor-interference (i.e., using sitting as the single-task reference for cognitive-task performance, see below). This 60s seated subtraction task was randomized with the six walking conditions.
Outcome measures
The primary outcome measure was walking speed (m/s) as determined with the standard 10MWT, 10MWT context and IWW obstacles trials (m/s), averaged over repetitions. Secondary outcome measures were walking adaptability, cognitive dual-task performance (the number of correct subtractions per second; sub/s) and cognitive-motor interference (dual-task effects), averaged over repetitions (Fig. 2). For the 10MWT context, walking adaptability was the sum of sub-scores obtained for obstacle avoidance, tandem walking and targeted stepping, averaged over the three repetitions (range 0–10, 1 point per obstacle, 1 point per target and max 4 points for tandem walking). Details regarding the walking-adaptability score can be found in [27]. The walking-adaptability score of the IWW obstacles was the sum of the points received for the first 10 obstacles to obtain the same scoring range as for the 10MWT context assessment (range 0–10). Walking speed and cognitive dual-task performance of this assessment was also averaged over the trials involving the first 10 projected obstacles (i.e., excluding dummy trials). Walking adaptability was scored manually by two observers through visual inspection of sagittal video recordings and averaged in case of discrepancies. Cognitive-motor interference during dual-task walking was quantified using the average of the respective dual-task effects of walking speed, the walking-adaptability score and the cognitive-task performance (with sitting as single-task reference), that is, motor (walking speed, walking adaptability) and cognitive scores were combined to reflect overall task performance. Following [28], dual-task effects were defined as 100% * (dual-task performance – single-task performance)/single-task performance, with a negative cognitive-motor interference score indicating overall poorer dual-task than single-task performance.
Furthermore, participants’ experience and attitude towards the interventions were assessed with a purpose-designed evaluation questionnaire consisting of 1–10 rating scales and multiple-choice questions assessing participants’ experience, attitude towards the interventions, improvements, and discomforts during and after training (see Appendix 1).
Finally, to test the expectation of different amounts of walking practice per session between CT and FP, we compared the total number of steps and the number of adaptive steps taken per session for two subgroups (CT n = 10 and FP n = 10). This process measure was obtained using the treadmill’s inbuilt step counter (CT) and by counting the number of steps (FP) using video recordings of a random selection of training sessions by two observers (averaged in case of discrepancies).
Statistical analysis
Participant characteristics and baseline performance were compared between the two groups using independent t-tests for normally distributed interval variables, Mann-Whitney U-tests for ordinal and non-normal interval variables and Fisher’s exact tests for nominal variables. To analyze the change over time in walking speed (standard and context-specific), walking adaptability, cognitive dual-task performance and cognitive-motor interference (for all participants, compared to baseline), we performed paired samples t-tests or Wilcoxon signed rank tests for ordinal or non-normally distributed variables at each time point (T1, T2 and T3). For comparing the effects of the interventions on the outcome measures, we calculated changes in outcome measures by subtracting baseline values from the values at each time point (T1, T2 and T3). These change scores of the outcome measures were analyzed using ANCOVA with correction for baseline values. We used a different statistical analysis (with correction for baseline values) compared to the one described in the study protocol [15], because of the large variation in the baseline (pre-intervention) outcome measures within the groups. We analyzed ordinal and non-normally distributed variables, notably the participants’ experience and attitude towards the interventions, using Mann-Whitney U-tests. The amount of walking practice was compared using independent t-tests for the total number of steps and the number of adaptive steps taken per training session. The level of significance was set at p < 0.05, while 0.05 < p < 0.075 was seen as a tendency towards significance. Effect sizes are presented as partial ƞ2 for ANCOVA or r for the other tests. This trial was not an intention-to-treat analysis because dropouts were excluded from the analysis and only complete case data were used.